{"id":"W2897820198","doi":"10.1007/s00170-018-2651-0","title":"Tool wear characterization in high-speed milling of titanium metal matrix composites","year":2018,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":26,"is_retracted":false,"has_abstract":false,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Materials science; Machinability; Abrasive; Tool wear; Insert (composites); Abrasion (mechanical); Machining; Surface roughness; Carbide; Titanium carbide; Metallurgy; Composite material; Ceramic; Surface finish; Titanium","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001308166,0.0001098128,0.0001961235,0.0003983865,0.00002936983,0.00001423094,0.0004826091,0.00007061422,0.00002467218],"category_scores_gemma":[0.00005247564,0.00008820778,0.00004013971,0.0001380158,0.00007952716,0.0002145145,0.00006564974,0.0002320792,0.000003505983],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007975783,"about_ca_system_score_gemma":0.00001277305,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001940759,"about_ca_topic_score_gemma":0.00000395392,"domain_scores_codex":[0.9991431,0.00000852386,0.0004443562,0.00008254665,0.0001943467,0.0001271318],"domain_scores_gemma":[0.9993555,0.00004761351,0.0002805026,0.000114011,0.0001889946,0.00001339581],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001010567,0.00001926657,0.0001497518,0.0000148226,0.00006761931,0.000007949613,0.00009463082,0.3468741,0.6428288,0.001136129,0.000002804147,0.008703083],"study_design_scores_gemma":[0.0005503973,0.0001140317,0.0008361597,0.0001088026,0.00001392783,0.00006283036,0.00007757124,0.009966147,0.9836801,0.003960744,0.0005330553,0.00009619277],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9044012,0.0001165036,0.09417602,0.0004084429,0.0007187298,0.00006304961,0.000007584656,0.00006440625,0.00004400693],"genre_scores_gemma":[0.9662317,0.000329093,0.033227,0.00002101531,0.0001426431,0.000001335058,0.000007136015,0.00001996578,0.00002010124],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3408513,"threshold_uncertainty_score":0.3597009,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0043951798218034,"score_gpt":0.2327318123968942,"score_spread":0.2283366325750908,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}